Linear regression is basically finding the best fitting line for the data points provided
- The equation for linear regression is Y = β0 + β1X1 + β2X2 + … + βnXn + ε
- Where:
- Y is the dependent variable.
- X1, X2, …, Xn are the independent variables.
- β0 is the intercept.
- β1, β2, …, βn are the coefficients.
- ε represents the noise.
Observation from the Datasheet:
The dataset exhibits the factors such as Diabetes , Obesity and Inactivity for all the states in the country of USA for a particular year i.e 2018.But the number of samples for diabetes, obesity and inactivity are not same.